Subordinated exchange rate models: Evidence for heavy tailed distributions and long-range dependence

C. Marinelli, S. T. Rachev, R. Roll

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

We investigate the main properties of high-frequency exchange rate data in the setting of stochastic subordination and stable modeling, focusing on heavy-tailedness and long memory, together with their dependence on the sampling period. We show that the intrinsic time process exhibits strong long-range dependence and has increments well described by a Weibull law, while the return series in intrinsic time has weak long memory and is well approximated by a stable Lévy motion. We also show that the stable domain of attraction offers a good fit to the returns in physical time, which leads us to consider as a realistic model for exchange rate data a process Z(t) subordinated to an α-stable Lévy motion S(t) (possibly fractional stable) by a long-memory intrinsic time process T(t) with Weibull-distributed increments.

Original languageEnglish
Pages (from-to)955-1001
Number of pages47
JournalMathematical and Computer Modelling
Volume34
Issue number9-11
DOIs
StatePublished - Sep 24 2001

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